Wenjie Lu

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About

Wenjie Lu is a researcher working at the intersection of neurotechnology, human-machine interaction, and robotics, with a focus on leveraging electroencephalography (EEG) signals to enable direct neural control of physical systems. Lu's most notable contribution is the development of a brain-machine interface (BMI) framework that translates raw EEG brain activity — captured using the consumer-grade Emotiv EPOC headset — into actionable commands for controlling a robotic arm, specifically the Robai Cyton system. This work, published in 2015 and cited 16 times, represents a meaningful step toward accessible, non-invasive neural control technologies, demonstrating that thought recognition software can be effectively designed, built, and validated in a practical robotic context. By bridging the gap between cognitive intent and mechanical execution, Lu's research contributes to the broader field of assistive technology, with promising implications for individuals with motor disabilities seeking greater autonomy through neural interfaces. The work underscores the growing potential of affordable EEG hardware as a platform for serious scientific and engineering applications, making sophisticated brain-computer interaction more accessible to researchers and end users alike.